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Rendering-a-Dynamic-AI-Chatbot-using-Streamlit\n## OpenAI Large Language Model (LLM) powered Chatbot using Streamlit\n\nThis project involves creating an AI chatbot that can take on different personas, keep track of conversation history, and provide coherent responses.\nThe Chatbot is then rendered using [Streamlit](https://streamlit.io/).\n\nKey skills we'll practice include:\n\n* Using the **OpenAI API** to interact with a large language model.\n* Crafting and managing distinct chatbot **personas with system messages**.\n* Monitoring and handling **token usage to stay within a token budget**.\n* Maintaining a **conversation history to achieve contextually aware interactions**.\n\n### Creating the Chatbot Framework\nThe Chatbot Framework is implementated as a **ConversationManager** class in the module `conversation_manager.py` while the rendering using [Streamlit](https://streamlit.io/) is implemented in `chatbot_using_streamlit.py`\n\nTo test the bot from your local machine run 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